Flanagan, Larry
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Browsing Flanagan, Larry by Author "Desai, Ankur R."
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- ItemImpact of hydrological variations on modeling of peatland CO2 fluxes: results from the North American Carbon Program site synthesis(American Geophysical Union, 2012) Sulman, Benjamin N.; Desai, Ankur R.; Schroeder, Nicole M.; Ricciuto, Daniel M.; Barr, Alan G.; Richardson, Andrew D.; Flanagan, Larry B.; Lafleur, Peter M.; Tian, Hanqin; Chen, Guangsheng; Grant, Robert F.; Poulter, Benjamin; Verbeeck, Hans; Ciais, Philippe; Ringeval, Bruno; Baker, Ian T.; Schaefer, Kevin; Luo, Yiqi; Wong, EnshengNorthern peatlands are likely to be important in future carbon cycle-climate feedbacks due to their large carbon pools and vulnerability to hydrological change. Use of non-peatland-specific models could lead to bias in modeling studies of peatland-rich regions. Here, seven ecosystem models were used to simulate CO2 fluxes at three wetland sites in Canada and the northern United States, including two nutrient-rich fens and one nutrient-poor, sphagnum-dominated bog, over periods between 1999 and 2007. Models consistently overestimated mean annual gross ecosystem production (GEP) and ecosystem respiration (ER) at all three sites. Monthly flux residuals (simulated – observed) were correlated with measured water table for GEP and ER at the two fen sites, but were not consistently correlated with water table at the bog site. Models that inhibited soil respiration under saturated conditions had less mean bias than models that did not. Modeled diurnal cycles agreed well with eddy covariance measurements at fen sites, but overestimated fluxes at the bog site. Eddy covariance GEP and ER at fens were higher during dry periods than during wet periods, while models predicted either the opposite relationship or no significant difference. At the bog site, eddy covariance GEP did not depend on water table, while simulated GEP was higher during wet periods. Carbon cycle modeling in peatland-rich regions could be improved by incorporating wetland-specific hydrology and by inhibiting GEP and ER under saturated conditions. Bogs and fens likely require distinct plant and soil parameterizations in ecosystem models due to differences in nutrients, peat properties, and plant communities.
- ItemA model-data intercomparison of CO2 exchange across North America: results from the North American Carbon Program site synthesis(American Geophysical Union, 2010) Schwalm, Christopher R.; Williams, Christopher A.; Schaefer, Kevin; Anderson, Ryan S.; Arain, M. Altaf; Baker, Ian T.; Barr, Alan G.; Black, T. Andrew; Chen, Guangsheng; Chen, Jing M.; Ciais, Philippe; Davis, Kenneth J.; Desai, Ankur R.; Dietze, Michael C.; Dragoni, Danilo; Fischer, Marc L.; Flanagan, Larry B.; Grant, Robert F.; Gu, Lianhong; Hollinger, David Y.; Izaurralde, R. Cesar; Kucharik, Christopher J.; Lafleur, Peter M.; Law, Beverly E.; Li, Longhui; Li, Zhengpeng; Liu, Shuguang; Lokupitiya, Erandathie; Luo, Yiqi; Ma, Siyan; Margolis, Hank; Matamala, Roser; McCaughey, Harry; Monson, Russell K.; Oechel, Walter C.; Peng, Changhui; Poulter, Benjamin; Price, David T.; Ricciuto, Daniel M.; Riley, William J.; Sahoo, Alok Kumar; Sprintsin, Michael; Sun, Jianfeng; Tian, Hanqin; Tonitto, Christina; Verbeeck, Hans; Verma, Shashi B.Our current understanding of terrestrial carbon processes is represented in various models used to integrate and scale measurements of CO2 exchange from remote sensing and other spatiotemporal data. Yet assessments are rarely conducted to determine how well models simulate carbon processes across vegetation types and environmental conditions. Using standardized data from the North American Carbon Program we compare observed and simulated monthly CO2 exchange from 44 eddy covariance flux towers in North America and 22 terrestrial biosphere models. The analysis period spans ∼220 site‐years, 10 biomes, and includes two large‐scale drought events, providing a natural experiment to evaluate model skill as a function of drought and seasonality. We evaluate models’ ability to simulate the seasonal cycle of CO2 exchange using multiple model skill metrics and analyze links between model characteristics, site history, and model skill. Overall model performance was poor; the difference between observations and simulations was ∼10 times observational uncertainty, with forested ecosystems better predicted than nonforested. Model‐data agreement was highest in summer and in temperate evergreen forests. In contrast, model performance declined in spring and fall, especially in ecosystems with large deciduous components, and in dry periods during the growing season. Models used across multiple biomes and sites, the mean model ensemble, and a model using assimilated parameter values showed high consistency with observations. Models with the highest skill across all biomes all used prescribed canopy phenology, calculated NEE as the difference between GPP and ecosystem respiration, and did not use a daily time step.